This new record demonstrates how SiSense technology can analyze 100 times more data than traditional in-memory solutions, at a fraction of the cost, and how it democratizes Big Data Analytics by providing businesses of all sizes with everything they need in one package. The server used for this performance is an "off-the-shelf" Dell PowerEdge R720 Rack Server, and SiSense shows it can analyze on one node what normally requires 20 nodes.

The company is also a finalist in the conference's "Startup Showcase" competition taking place Tuesday, Feb. 26 at 6:00pm PST.

"The majority of businesses struggle with Terabytes of Data, not Petabytes. And they shouldn't have to worry about setting up complex clusters and distributed environments that were initially designed for Petabyte scale," says Amit Bendov, SiSense CEO. "With this record, we show that the answer can be very simple: our software provides the scale they need on one server and it contains the entire solution, in one package; from the database to beautiful visualizations on the web." Bendov continues: "We want to show that Data Analytics is not just reserved for the few companies that can afford complex systems. We aim to make Big Data Analytics approachable and simple for all."
SiSense Secret SauceThe secret is SiSense's unique technology, the ElastiCube™, a high-performance analytical database that leverages the latest innovation in hardware to maximize machine RAM and CPU use. "The ElastiCube is exceptionally efficient at harnessing machine capacity that typically goes untapped," says Bendov.

Wayne Eckerson, an industry thought leader and the founder of BI Leadership Research highlights: "One of the key innovations I was impressed with, is the way SiSense combines vectorization, in-memory and columnar algebra to boost query performance -- this is a very different and new approach."
SiSense Prism's columnar data structure and compression algorithms provide great storage improvements. Its compiler runs inside the CPU and inside the machine control unit, and decides in real-time how to best execute queries -- either in RAM, Disk, or both. SiSense also uses "vectorization," a process that refers to a machine's ability to apply the same operation to multiple pieces of data simultaneously, resulting in immediate performance gains.

A Big Data Analytics Revolution"Big Data Analytics is in need of a Revolution. Two weeks ago, we organized an event that included customers and companies of all sizes from Wix to Facebook to Netflix, and SurveyMonkey. Regardless of their size, companies consistently complain about the same issue: Big Data Analytics is too complicated," said Bendov.

SiSense boasts a fast-growing list of customers, spanning across 48 countries. It includes very large companies like Merck, ESPN, and NASA to Silicon Valley icons like Yahoo! or Fusion-IO, to small companies like Uber or Fiverr. SiSense Prism can be deployed on-premises or in the cloud.